git.sesse.net Git - c64tapwav/blob - decode.cpp

   1 // Copyright Steinar H. Gunderson <sgunderson@bigfoot.com>
   2 // Licensed under the GPL, v2. (See the file COPYING.)
   3
   4 #include <stdio.h>
   5 #include <string.h>
   6 #include <math.h>
   7 #include <assert.h>
   8 #include <limits.h>
   9 #include <getopt.h>
  10 #include <vector>
  11 #include <algorithm>
  12
  13 #include "audioreader.h"
  14 #include "interpolate.h"
  15 #include "level.h"
  16 #include "tap.h"
  17 #include "filter.h"
  18
  19 #define BUFSIZE 4096
  20 #define C64_FREQUENCY 985248
  21 #define SYNC_PULSE_START 1000
  22 #define SYNC_PULSE_END 20000
  23 #define SYNC_PULSE_LENGTH 378.0
  24 #define SYNC_TEST_TOLERANCE 1.10
  25
  26 // SPSA options
  27 #define NUM_FILTER_COEFF 32
  28 #define NUM_SPSA_VALS (NUM_FILTER_COEFF + 2)
  29 #define NUM_ITER 5000
  30 #define A NUM_ITER/10  // approx
  31 #define INITIAL_A 0.005 // A bit of trial and error...
  32 #define INITIAL_C 0.02  // This too.
  33 #define GAMMA 0.166
  34 #define ALPHA 1.0
  35
  36 static float hysteresis_upper_limit = 0.1;
  37 static float hysteresis_lower_limit = -0.1;
  38 static bool do_calibrate = true;
  39 static bool output_cycles_plot = false;
  40 static bool do_crop = false;
  41 static float crop_start = 0.0f, crop_end = HUGE_VAL;
  42
  43 static bool use_fir_filter = false;
  44 static float filter_coeff[NUM_FILTER_COEFF] = { 1.0f };  // The rest is filled with 0.
  45 static bool use_rc_filter = false;
  46 static float rc_filter_freq;
  47 static bool output_filtered = false;
  48
  49 static bool quiet = false;
  50 static bool do_auto_level = false;
  51 static bool output_leveled = false;
  52 static std::vector<float> train_snap_points;
  53 static bool do_train = false;
  54
  55 // The frequency to filter on (for do_auto_level), in Hertz.
  56 // Larger values makes the compressor react faster, but if it is too large,
  57 // you'll ruin the waveforms themselves.
  58 static float auto_level_freq = 200.0;
  59
  60 // The minimum estimated sound level (for do_auto_level) at any given point.
  61 // If you decrease this, you'll be able to amplify really silent signals
  62 // by more, but you'll also increase the level of silent (ie. noise-only) segments,
  63 // possibly caused misdetected pulses in these segments.
  64 static float min_level = 0.05f;
  65
  66 // search for the value <limit> between [x,x+1]
  67 double find_crossing(const std::vector<float> &pcm, int x, float limit)
  68 {
  69         double upper = x;
  70         double lower = x + 1;
  71         while (lower - upper > 1e-3) {
  72                 double mid = 0.5f * (upper + lower);
  73                 if (lanczos_interpolate(pcm, mid) > limit) {
  74                         upper = mid;
  75                 } else {
  76                         lower = mid;
  77                 }
  78         }
  79
  80         return 0.5f * (upper + lower);
  81 }
  82
  83 struct pulse {
  84         double time;  // in seconds from start
  85         double len;   // in seconds
  86 };
  87
  88 // Calibrate on the first ~25k pulses (skip a few, just to be sure).
  89 double calibrate(const std::vector<pulse> &pulses) {
  90         if (pulses.size() < SYNC_PULSE_END) {
  91                 fprintf(stderr, "Too few pulses, not calibrating!\n");
  92                 return 1.0;
  93         }
  94
  95         int sync_pulse_end = -1;
  96         double sync_pulse_stddev = -1.0;
  97
  98         // Compute the standard deviation (to check for uneven speeds).
  99         // If it suddenly skyrockets, we assume that sync ended earlier
 100         // than we thought (it should be 25000 cycles), and that we should
 101         // calibrate on fewer cycles.
 102         for (int try_end : { 2000, 4000, 5000, 7500, 10000, 15000, SYNC_PULSE_END }) {
 103                 double sum2 = 0.0;
 104                 for (int i = SYNC_PULSE_START; i < try_end; ++i) {
 105                         double cycles = pulses[i].len * C64_FREQUENCY;
 106                         sum2 += (cycles - SYNC_PULSE_LENGTH) * (cycles - SYNC_PULSE_LENGTH);
 107                 }
 108                 double stddev = sqrt(sum2 / (try_end - SYNC_PULSE_START - 1));
 109                 if (sync_pulse_end != -1 && stddev > 5.0 && stddev / sync_pulse_stddev > 1.3) {
 110                         fprintf(stderr, "Stopping at %d sync pulses because standard deviation would be too big (%.2f cycles); shorter-than-usual trailer?\n",
 111                                 sync_pulse_end, stddev);
 112                         break;
 113                 }
 114                 sync_pulse_end = try_end;
 115                 sync_pulse_stddev = stddev;
 116         }
 117         if (!quiet) {
 118                 fprintf(stderr, "Sync pulse length standard deviation: %.2f cycles\n",
 119                         sync_pulse_stddev);
 120         }
 121
 122         double sum = 0.0;
 123         for (int i = SYNC_PULSE_START; i < sync_pulse_end; ++i) {
 124                 sum += pulses[i].len;
 125         }
 126         double mean_length = C64_FREQUENCY * sum / (sync_pulse_end - SYNC_PULSE_START);
 127         double calibration_factor = SYNC_PULSE_LENGTH / mean_length;
 128         if (!quiet) {
 129                 fprintf(stderr, "Calibrated sync pulse length: %.2f -> %.2f (change %+.2f%%)\n",
 130                         mean_length, SYNC_PULSE_LENGTH, 100.0 * (calibration_factor - 1.0));
 131         }
 132
 133         // Check for pulses outside +/- 10% (sign of misdetection).
 134         for (int i = SYNC_PULSE_START; i < sync_pulse_end; ++i) {
 135                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 136                 if (cycles < SYNC_PULSE_LENGTH / SYNC_TEST_TOLERANCE || cycles > SYNC_PULSE_LENGTH * SYNC_TEST_TOLERANCE) {
 137                         fprintf(stderr, "Sync cycle with downflank at %.6f was detected at %.0f cycles; misdetect?\n",
 138                                 pulses[i].time, cycles);
 139                 }
 140         }
 141
 142         return calibration_factor;
 143 }
 144
 145 void output_tap(const std::vector<pulse>& pulses, double calibration_factor)
 146 {
 147         std::vector<char> tap_data;
 148         for (unsigned i = 0; i < pulses.size(); ++i) {
 149                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 150                 int len = lrintf(cycles / TAP_RESOLUTION);
 151                 if (i > SYNC_PULSE_END && (cycles < 100 || cycles > 800)) {
 152                         fprintf(stderr, "Cycle with downflank at %.6f was detected at %.0f cycles; misdetect?\n",
 153                                         pulses[i].time, cycles);
 154                 }
 155                 if (len <= 255) {
 156                         tap_data.push_back(len);
 157                 } else {
 158                         int overflow_len = lrintf(cycles);
 159                         tap_data.push_back(0);
 160                         tap_data.push_back(overflow_len & 0xff);
 161                         tap_data.push_back((overflow_len >> 8) & 0xff);
 162                         tap_data.push_back(overflow_len >> 16);
 163                 }
 164         }
 165
 166         tap_header hdr;
 167         memcpy(hdr.identifier, "C64-TAPE-RAW", 12);
 168         hdr.version = 1;
 169         hdr.reserved[0] = hdr.reserved[1] = hdr.reserved[2] = 0;
 170         hdr.data_len = tap_data.size();
 171
 172         fwrite(&hdr, sizeof(hdr), 1, stdout);
 173         fwrite(tap_data.data(), tap_data.size(), 1, stdout);
 174 }
 175
 176 static struct option long_options[] = {
 177         {"auto-level",       0,                 0, 'a' },
 178         {"auto-level-freq",  required_argument, 0, 'b' },
 179         {"output-leveled",   0,                 0, 'A' },
 180         {"min-level",        required_argument, 0, 'm' },
 181         {"no-calibrate",     0,                 0, 's' },
 182         {"plot-cycles",      0,                 0, 'p' },
 183         {"hysteresis-limit", required_argument, 0, 'l' },
 184         {"filter",           required_argument, 0, 'f' },
 185         {"rc-filter",        required_argument, 0, 'r' },
 186         {"output-filtered",  0,                 0, 'F' },
 187         {"crop",             required_argument, 0, 'c' },
 188         {"quiet",            0,                 0, 'q' },
 189         {"help",             0,                 0, 'h' },
 190         {0,                  0,                 0, 0   }
 191 };
 192
 193 void help()
 194 {
 195         fprintf(stderr, "decode [OPTIONS] AUDIO-FILE > TAP-FILE\n");
 196         fprintf(stderr, "\n");
 197         fprintf(stderr, "  -a, --auto-level             automatically adjust amplitude levels throughout the file\n");
 198         fprintf(stderr, "  -b, --auto-level-freq        minimum frequency in Hertz of corrected level changes (default 200 Hz)\n");
 199         fprintf(stderr, "  -A, --output-leveled         output leveled waveform to leveled.raw\n");
 200         fprintf(stderr, "  -m, --min-level              minimum estimated sound level (0..1) for --auto-level\n");
 201         fprintf(stderr, "  -s, --no-calibrate           do not try to calibrate on sync pulse length\n");
 202         fprintf(stderr, "  -p, --plot-cycles            output debugging info to cycles.plot\n");
 203         fprintf(stderr, "  -l, --hysteresis-limit U[:L] change amplitude threshold for ignoring pulses (-1..1)\n");
 204         fprintf(stderr, "  -f, --filter C1:C2:C3:...    specify FIR filter (up to %d coefficients)\n", NUM_FILTER_COEFF);
 205         fprintf(stderr, "  -r, --rc-filter FREQ         send signal through a highpass RC filter with given frequency (in Hertz)\n");
 206         fprintf(stderr, "  -F, --output-filtered        output filtered waveform to filtered.raw\n");
 207         fprintf(stderr, "  -c, --crop START[:END]       use only the given part of the file\n");
 208         fprintf(stderr, "  -t, --train LEN1:LEN2:...    train a filter for detecting any of the given number of cycles\n");
 209         fprintf(stderr, "                               (implies --no-calibrate and --quiet unless overridden)\n");
 210         fprintf(stderr, "  -q, --quiet                  suppress some informational messages\n");
 211         fprintf(stderr, "  -h, --help                   display this help, then exit\n");
 212         exit(1);
 213 }
 214
 215 void parse_options(int argc, char **argv)
 216 {
 217         for ( ;; ) {
 218                 int option_index = 0;
 219                 int c = getopt_long(argc, argv, "ab:Am:spl:f:r:Fc:t:qh", long_options, &option_index);
 220                 if (c == -1)
 221                         break;
 222
 223                 switch (c) {
 224                 case 'a':
 225                         do_auto_level = true;
 226                         break;
 227
 228                 case 'b':
 229                         auto_level_freq = atof(optarg);
 230                         break;
 231
 232                 case 'A':
 233                         output_leveled = true;
 234                         break;
 235
 236                 case 'm':
 237                         min_level = atof(optarg);
 238                         break;
 239
 240                 case 's':
 241                         do_calibrate = false;
 242                         break;
 243
 244                 case 'p':
 245                         output_cycles_plot = true;
 246                         break;
 247
 248                 case 'l': {
 249                         const char *hyststr = strtok(optarg, ": ");
 250                         hysteresis_upper_limit = atof(hyststr);
 251                         hyststr = strtok(NULL, ": ");
 252                         if (hyststr == NULL) {
 253                                 hysteresis_lower_limit = -hysteresis_upper_limit;
 254                         } else {
 255                                 hysteresis_lower_limit = atof(hyststr);
 256                         }
 257                         break;
 258                 }
 259
 260                 case 'f': {
 261                         const char *coeffstr = strtok(optarg, ": ");
 262                         int coeff_index = 0;
 263                         while (coeff_index < NUM_FILTER_COEFF && coeffstr != NULL) {
 264                                 filter_coeff[coeff_index++] = atof(coeffstr);
 265                                 coeffstr = strtok(NULL, ": ");
 266                         }
 267                         use_fir_filter = true;
 268                         break;
 269                 }
 270
 271                 case 'r':
 272                         use_rc_filter = true;
 273                         rc_filter_freq = atof(optarg);
 274                         break;
 275
 276                 case 'F':
 277                         output_filtered = true;
 278                         break;
 279
 280                 case 'c': {
 281                         const char *cropstr = strtok(optarg, ":");
 282                         crop_start = atof(cropstr);
 283                         cropstr = strtok(NULL, ":");
 284                         if (cropstr == NULL) {
 285                                 crop_end = HUGE_VAL;
 286                         } else {
 287                                 crop_end = atof(cropstr);
 288                         }
 289                         do_crop = true;
 290                         break;
 291                 }
 292
 293                 case 't': {
 294                         const char *cyclestr = strtok(optarg, ":");
 295                         while (cyclestr != NULL) {
 296                                 train_snap_points.push_back(atof(cyclestr));
 297                                 cyclestr = strtok(NULL, ":");
 298                         }
 299                         do_train = true;
 300
 301                         // Set reasonable defaults (can be overridden later on the command line).
 302                         do_calibrate = false;
 303                         quiet = true;
 304                         break;
 305                 }
 306
 307                 case 'q':
 308                         quiet = true;
 309                         break;
 310
 311                 case 'h':
 312                 default:
 313                         help();
 314                         exit(1);
 315                 }
 316         }
 317 }
 318
 319 std::vector<float> crop(const std::vector<float>& pcm, float crop_start, float crop_end, int sample_rate)
 320 {
 321         size_t start_sample, end_sample;
 322         if (crop_start >= 0.0f) {
 323                 start_sample = std::min<size_t>(lrintf(crop_start * sample_rate), pcm.size());
 324         }
 325         if (crop_end >= 0.0f) {
 326                 end_sample = std::min<size_t>(lrintf(crop_end * sample_rate), pcm.size());
 327         }
 328         return std::vector<float>(pcm.begin() + start_sample, pcm.begin() + end_sample);
 329 }
 330
 331 // TODO: Support AVX here.
 332 std::vector<float> do_fir_filter(const std::vector<float>& pcm, const float* filter)
 333 {
 334         std::vector<float> filtered_pcm;
 335         filtered_pcm.reserve(pcm.size());
 336         for (unsigned i = NUM_FILTER_COEFF; i < pcm.size(); ++i) {
 337                 float s = 0.0f;
 338                 for (int j = 0; j < NUM_FILTER_COEFF; ++j) {
 339                         s += filter[j] * pcm[i - j];
 340                 }
 341                 filtered_pcm.push_back(s);
 342         }
 343
 344         if (output_filtered) {
 345                 FILE *fp = fopen("filtered.raw", "wb");
 346                 fwrite(filtered_pcm.data(), filtered_pcm.size() * sizeof(filtered_pcm[0]), 1, fp);
 347                 fclose(fp);
 348         }
 349
 350         return filtered_pcm;
 351 }
 352
 353 std::vector<float> do_rc_filter(const std::vector<float>& pcm, float freq, int sample_rate)
 354 {
 355         // This is only a 6 dB/oct filter, which seemingly works better
 356         // than the Filter class, which is a standard biquad (12 dB/oct).
 357         // The b/c calculations come from libnyquist (atone.c);
 358         // I haven't checked, but I suppose they fall out of the bilinear
 359         // transform of the transfer function H(s) = s/(s + w).
 360         std::vector<float> filtered_pcm;
 361         filtered_pcm.resize(pcm.size());
 362         const float b = 2.0f - cos(2.0 * M_PI * freq / sample_rate);
 363         const float c = b - sqrt(b * b - 1.0f);
 364         float prev_in = 0.0f;
 365         float prev_out = 0.0f;
 366         for (unsigned i = 0; i < pcm.size(); ++i) {
 367                 float in = pcm[i];
 368                 float out = c * (prev_out + in - prev_in);
 369                 filtered_pcm[i] = out;
 370                 prev_in = in;
 371                 prev_out = out;
 372         }
 373
 374         if (output_filtered) {
 375                 FILE *fp = fopen("filtered.raw", "wb");
 376                 fwrite(filtered_pcm.data(), filtered_pcm.size() * sizeof(filtered_pcm[0]), 1, fp);
 377                 fclose(fp);
 378         }
 379
 380         return filtered_pcm;
 381 }
 382
 383 std::vector<pulse> detect_pulses(const std::vector<float> &pcm, float hysteresis_upper_limit, float hysteresis_lower_limit, int sample_rate)
 384 {
 385         std::vector<pulse> pulses;
 386
 387         // Find the flanks.
 388         enum State { START, ABOVE, BELOW } state = START;
 389         double last_downflank = -1;
 390         for (unsigned i = 0; i < pcm.size(); ++i) {
 391                 if (pcm[i] > hysteresis_upper_limit) {
 392                         state = ABOVE;
 393                 } else if (pcm[i] < hysteresis_lower_limit) {
 394                         if (state == ABOVE) {
 395                                 // down-flank!
 396                                 double t = find_crossing(pcm, i - 1, hysteresis_lower_limit) * (1.0 / sample_rate) + crop_start;
 397                                 if (last_downflank > 0) {
 398                                         pulse p;
 399                                         p.time = t;
 400                                         p.len = t - last_downflank;
 401                                         pulses.push_back(p);
 402                                 }
 403                                 last_downflank = t;
 404                         }
 405                         state = BELOW;
 406                 }
 407         }
 408         return pulses;
 409 }
 410
 411 void output_cycle_plot(const std::vector<pulse> &pulses, double calibration_factor)
 412 {
 413         FILE *fp = fopen("cycles.plot", "w");
 414         for (unsigned i = 0; i < pulses.size(); ++i) {
 415                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 416                 fprintf(fp, "%f %f\n", pulses[i].time, cycles);
 417         }
 418         fclose(fp);
 419 }
 420
 421 std::pair<int, double> find_closest_point(double x, const std::vector<float> &points)
 422 {
 423         int best_point = 0;
 424         double best_dist = (x - points[0]) * (x - points[0]);
 425         for (unsigned j = 1; j < train_snap_points.size(); ++j) {
 426                 double dist = (x - points[j]) * (x - points[j]);
 427                 if (dist < best_dist) {
 428                         best_point = j;
 429                         best_dist = dist;
 430                 }
 431         }
 432         return std::make_pair(best_point, best_dist);
 433 }
 434
 435 float eval_badness(const std::vector<pulse>& pulses, double calibration_factor)
 436 {
 437         double sum_badness = 0.0;
 438         for (unsigned i = 0; i < pulses.size(); ++i) {
 439                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 440                 if (cycles > 2000.0) cycles = 2000.0;  // Don't make pauses arbitrarily bad.
 441                 std::pair<int, double> selected_point_and_sq_dist = find_closest_point(cycles, train_snap_points);
 442                 sum_badness += selected_point_and_sq_dist.second;
 443         }
 444         return sqrt(sum_badness / (pulses.size() - 1));
 445 }
 446
 447 void find_kmeans(const std::vector<pulse> &pulses, double calibration_factor, const std::vector<float> &initial_centers)
 448 {
 449         std::vector<float> last_centers = initial_centers;
 450         std::vector<float> sums;
 451         std::vector<float> num;
 452         sums.resize(initial_centers.size());
 453         num.resize(initial_centers.size());
 454         for ( ;; ) {
 455                 for (unsigned i = 0; i < initial_centers.size(); ++i) {
 456                         sums[i] = 0.0f;
 457                         num[i] = 0;
 458                 }
 459                 for (unsigned i = 0; i < pulses.size(); ++i) {
 460                         double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 461                         // Ignore heavy outliers, which are almost always long pauses.
 462                         if (cycles > 2000.0) {
 463                                 continue;
 464                         }
 465                         std::pair<int, double> selected_point_and_sq_dist = find_closest_point(cycles, last_centers);
 466                         int p = selected_point_and_sq_dist.first;
 467                         sums[p] += cycles;
 468                         ++num[p];
 469                 }
 470                 bool any_moved = false;
 471                 for (unsigned i = 0; i < initial_centers.size(); ++i) {
 472                         if (num[i] == 0) {
 473                                 fprintf(stderr, "K-means broke down, can't output new reference training points\n");
 474                                 return;
 475                         }
 476                         float new_center = sums[i] / num[i];
 477                         if (fabs(new_center - last_centers[i]) > 1e-3) {
 478                                 any_moved = true;
 479                         }
 480                         last_centers[i] = new_center;
 481                 }
 482                 if (!any_moved) {
 483                         break;
 484                 }
 485         }
 486         fprintf(stderr, "New reference training points:");
 487         for (unsigned i = 0; i < last_centers.size(); ++i) {
 488                 fprintf(stderr, " %.3f", last_centers[i]);
 489         }
 490         fprintf(stderr, "\n");
 491 }
 492
 493 void spsa_train(const std::vector<float> &pcm, int sample_rate)
 494 {
 495         float vals[NUM_SPSA_VALS] = { hysteresis_upper_limit, hysteresis_lower_limit, 1.0f };  // The rest is filled with 0.
 496
 497         float start_c = INITIAL_C;
 498         double best_badness = HUGE_VAL;
 499
 500         for (int n = 1; n < NUM_ITER; ++n) {
 501                 float a = INITIAL_A * pow(n + A, -ALPHA);
 502                 float c = start_c * pow(n, -GAMMA);
 503
 504                 // find a random perturbation
 505                 float p[NUM_SPSA_VALS];
 506                 float vals1[NUM_SPSA_VALS], vals2[NUM_SPSA_VALS];
 507                 for (int i = 0; i < NUM_SPSA_VALS; ++i) {
 508                         p[i] = (rand() % 2) ? 1.0 : -1.0;
 509                         vals1[i] = std::max(std::min(vals[i] - c * p[i], 1.0f), -1.0f);
 510                         vals2[i] = std::max(std::min(vals[i] + c * p[i], 1.0f), -1.0f);
 511                 }
 512
 513                 std::vector<pulse> pulses1 = detect_pulses(do_fir_filter(pcm, vals1 + 2), vals1[0], vals1[1], sample_rate);
 514                 std::vector<pulse> pulses2 = detect_pulses(do_fir_filter(pcm, vals2 + 2), vals2[0], vals2[1], sample_rate);
 515                 float badness1 = eval_badness(pulses1, 1.0);
 516                 float badness2 = eval_badness(pulses2, 1.0);
 517
 518                 // Find the gradient estimator
 519                 float g[NUM_SPSA_VALS];
 520                 for (int i = 0; i < NUM_SPSA_VALS; ++i) {
 521                         g[i] = (badness2 - badness1) / (2.0 * c * p[i]);
 522                         vals[i] -= a * g[i];
 523                         vals[i] = std::max(std::min(vals[i], 1.0f), -1.0f);
 524                 }
 525                 if (badness2 < badness1) {
 526                         std::swap(badness1, badness2);
 527                         std::swap(vals1, vals2);
 528                         std::swap(pulses1, pulses2);
 529                 }
 530                 if (badness1 < best_badness) {
 531                         fprintf(stderr, "\nNew best filter (badness=%f):", badness1);
 532                         for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
 533                                 fprintf(stderr, " %.5f", vals1[i + 2]);
 534                         }
 535                         fprintf(stderr, ", hysteresis limits = %f %f\n", vals1[0], vals1[1]);
 536                         best_badness = badness1;
 537
 538                         find_kmeans(pulses1, 1.0, train_snap_points);
 539
 540                         if (output_cycles_plot) {
 541                                 output_cycle_plot(pulses1, 1.0);
 542                         }
 543                 }
 544                 fprintf(stderr, "%d ", n);
 545                 fflush(stderr);
 546         }
 547 }
 548
 549 int main(int argc, char **argv)
 550 {
 551         parse_options(argc, argv);
 552
 553         make_lanczos_weight_table();
 554         std::vector<float> pcm;
 555         int sample_rate;
 556         if (!read_audio_file(argv[optind], &pcm, &sample_rate)) {
 557                 exit(1);
 558         }
 559
 560         if (do_crop) {
 561                 pcm = crop(pcm, crop_start, crop_end, sample_rate);
 562         }
 563
 564         if (use_fir_filter) {
 565                 pcm = do_fir_filter(pcm, filter_coeff);
 566         }
 567
 568         if (use_rc_filter) {
 569                 pcm = do_rc_filter(pcm, rc_filter_freq, sample_rate);
 570         }
 571
 572         if (do_auto_level) {
 573                 pcm = level_samples(pcm, min_level, auto_level_freq, sample_rate);
 574                 if (output_leveled) {
 575                         FILE *fp = fopen("leveled.raw", "wb");
 576                         fwrite(pcm.data(), pcm.size() * sizeof(pcm[0]), 1, fp);
 577                         fclose(fp);
 578                 }
 579         }
 580
 581 #if 0
 582         for (int i = 0; i < LEN; ++i) {
 583                 in[i] += rand() % 10000;
 584         }
 585 #endif
 586
 587 #if 0
 588         for (int i = 0; i < LEN; ++i) {
 589                 printf("%d\n", in[i]);
 590         }
 591 #endif
 592
 593         if (do_train) {
 594                 spsa_train(pcm, sample_rate);
 595                 exit(0);
 596         }
 597
 598         std::vector<pulse> pulses = detect_pulses(pcm, hysteresis_upper_limit, hysteresis_lower_limit, sample_rate);
 599
 600         double calibration_factor = 1.0;
 601         if (do_calibrate) {
 602                 calibration_factor = calibrate(pulses);
 603         }
 604
 605         if (output_cycles_plot) {
 606                 output_cycle_plot(pulses, calibration_factor);
 607         }
 608
 609         output_tap(pulses, calibration_factor);
 610 }